What Does Best-In-Class Mean in Sports?

Our role in the sports ecosystem affords us considerable opportunity to meet and learn from the best-in-breed operators and team owners in global sports. At the same time, several of us are newcomers to sports, having largely spent our careers investing in other target sectors or markets. From this vantage point, we’ve learned what’s truly unique about running a sports team (short answer: much) vs. other sectors.

We wanted to synthesize these learnings into a series of operating principles for sports franchise ownership and management. While there will be major exceptions based on the unique circumstances of each league, team, ownership group, or market, on average, we believe these rules hold true and that their implications are worth considering for all owners and operators.

We offer three principles to start, but we’ll revisit this theme on an ongoing basis.

Like any other business, a sports franchise sells a product, but unlike most businesses, it is not always obvious what it is. Is it a winning team? Is it the players or personalities on the team? The human drama of the sport? A special feeling or excitement among fans? Inclusiveness in a specific local culture or community? A family-friendly experience? A luxury or premium experience?

It can be all of the above, but in our view, the best sports management teams define their core values in such a way that the ideal product to be delivered to fans is (a) well defined and concrete, (b) embedded in your organization’s core values that govern talent assessment, and (c) is something that can be delivered consistently every year. This is standard, customer-centric management, but in the sports world, “the product” is somewhat amorphous – making it paramount that the team align on what it is.

Some choices of product definition are better than others. Very simply, if you are in a league where it is rational to expect to consistently produce a playoff-eligible, winning team, there is a larger problem of league design to consider. Otherwise, you must expect performance cycles. In fact, performance cycles are good: they are healthy and often necessary “expectation resets” for fans. While too much competitive balance can lead to outcomes too close to random chance for fans to care, the opposite extreme – constant dominance – dilutes the value of each individual game and eventually whole seasons for all teams, even the most dominant ones. While counterintuitive, and despite what fan surveys may suggest, constant team dominance year-in and year-out, in the extreme, yields diminishing returns over time. (This is an example of the ‘hedonic treadmill’ in cognitive psychology.)

Instead, define your product as something that fans will always want and pay for. What this is will be a function of your franchise, its legacy, and your market. Revenues are the best fuel for driving on-field performance and moderating inevitable performance cycles.

One quantitative perspective we’ve used internally to frame the debate about spending for performance is as follows. At first glance, it appears like customers and sponsors pay teams more - are willing to be charged higher prices - upon realization of strong on-field performance. But the reality is more complex. Instead, we think customers pay for two things: (1) rational expectations and (2) hope. A track record of success is evidence that expectations should be raised - with higher expectations comes monetization opportunities. But expectations have a ceiling. In addition, expectations can be (and due to randomness, sometimes will be) thwarted - sometimes, your team will simply fail to perform as expected. So priming expectations can take you only so far, and can be fragile. Instead, the best teams craft a ‘hope narrative’ that connects to but ultimately transcends on-field performance. A hope narrative is a web of commonly held associations among fans that drives emotions and beliefs about the team and the community of supporters that provides their motivation for ongoing commitment. This represents the largely emotional side of fandom. Our view is that the product definition is, in effect, a detailed reconstruction of what that hope narrative is, or perhaps should be. The management team is then empowered to execute so as to best craft and protect that narrative.

We posit that in no other business, except perhaps large-scale oil & gas exploration, are the appropriate horizons for assessing investment as long-term as in sports.

Well, that is a bit overstated. Some internal investments, e.g., a free agent signing, premium space redesign, or new marketing software, boil down to straightforward cost-benefit analyses where short-term payback is critical. Let’s get that out of the way.

But franchises are also brands (or ‘hope narratives’). As brands, they have long, complicated legacies to cultivate. And for any company anchored to a timeless brand, building brand equity is critical to growing value. This means that, while sometimes they must invest for short-term payoff (revenue-focus), teams must make investments with uncertain and unusually long-term payoffs. While the former are straightforward Excel calculations, the latter are not. In our experience, it is easy to slip from “revenue focus” to “brand focus” when discussing any business initiative, though they are different frames of reference.

While it is difficult to be quantitative about investments in brand equity, those conversations can still be rigorous – i.e., rules-based, logical, and structured. In our view, all teams should have a deliberate small, brand equity investment budget that is spent each year – in the form of things like:

The importance of long-term thinking is coming into focus with the opening of international markets for franchises in some leagues. In our view, these investments can be steady, relatively small, and yet add up to having extreme “right-tail” impacts on franchise revenue and value in the long-run. In most of these markets, there is no audience yet to monetize – a fan community must be built, sometimes from scratch. Building that audience requires patience – but one has to start sometime. (This can be a challenge for some teams, most of which come with an “installed base” of built-in local fan support that has developed over decades.)

What makes franchises so valuable is their timeless, evergreen quality as brand assets. Preserving and growing brand value requires a unique approach, a different vocabulary and a very long-term strategy.

While the sports business has evolved considerably in the post-Moneyball era, much of it – both team operations and business operations – remains human-driven and relationship-oriented.

This is bound to change in an age of AI. But it will be a slow process.

There’s one respect in which AI will not (or at least should not) impact the business: the game itself. AI will need to be tightly regulated to secure the integrity of the competition as a battle of specifically human ingenuity. People still play, learn, and compete in chess even though all grandmasters alive or dead would likely lose (at least on average) to the best-in-class chess-playing program. It is our human limitations that give the game meaning. As such, we are big believers in tightening the use of analytics and data science to compete on the field, with some exceptions.^[2] For example, we know it would be possible today to develop a football play-calling engine that maximizes game win-probability conditional on all prior in-game plays, both competing team rosters, and the entire history of all prior games ever played in the sport. Using GPT 4, one could interact with this model in real-time using natural language. Such a thing is currently banned, and we suspect it should be. But we already have the technology to effectively commoditize play-calling.

But on the business operations side, there is meaningful room to push the frontier. We view technology investment in simple terms. First, how can automation impact revenues? Those buckets include ticketing pricing automation and analytics, rate card optimization, activations, and marketing tech. Second, how can automation impact costs? Those buckets include all forms of workflow automation, digital content tooling, venue data capture, customer chat tools, and CRM. Finally, how can automation impact brand value? Those buckets are primarily focused on how to best equip the team’s digital/social outfit to maximize every opportunity to engage fans and drive affinity. That encompasses a lot. While automation for its own sake is a red herring, with the right business case underwriting it, tech spend can be a powerful value creation lever.

All business ops teams should be developing 5- and 10-year data strategy visions. Here are a few questions we would ask ourselves if we were making such a list. First, there are two foundational questions:

Once you settle that, a number of commercial avenues could open, possibly in partnership with a third party or built internally:

There are no easy answers here. Sports teams do not have large balance sheets that can absorb ambitious capex visions with uncertain P&L impact. Instead, we recommend starting small. Pick one area where your team could be executing better - earning more money, saving more money, or delighting fans more - and figure out all of the ways you would seek to do that; in the process, consider where ML/AI can play a role and then dedicate some of the exercise to pursuing that thread. And if you don’t have the data foundation in place, that can be a great place to start. The benefit of keeping these applications in mind is this: while AI-driven innovation will be slow, it is also largely inevitable. Keeping the foundations up-to-date while engaging in the day-to-day, hand-to-hand combat of the business is a great way to drive the change necessary to stay current if not innovate.

[1] Even if unsponsored, such investments can often have come with significant digital marketing payoff

[2] Another example: player valuation and assessment as a great area in which to allow AI to thrive, but only to a certain extent. It should be limited if and when all teams had exact or near-exact copies of the same, complete data sets and player valuation models – in that world, player valuation “arbitrage” goes to zero and all players are valued efficiently, making game outcomes largely random in a cap-floor system. In that extreme, very roughly speaking, all teams spend nearly the same amount on talent each year, and since all players are valued correctly, each team has equal levels of talent, and hence each team’s expected win-loss is .500.